//In this example we’ll look at how to implement a worker pool using goroutines and channels.

package main

import (
	"fmt"
	"time"
)

//Here’s the worker, of which we’ll run several concurrent instances.
//These workers will receive work on the jobs channel and send the corresponding results on results.
//We’ll sleep a second per job to simulate an expensive task.

func worker(id int, jobs <-chan int, results chan<- int) {
	for j := range jobs {
		fmt.Println("worker", id, "started  job", j)
		time.Sleep(time.Second)
		fmt.Println("worker", id, "finished job", j)
		results <- j * 2
	}
}
func main() {
	//In order to use our pool of workers we need to send them work and collect their results.
	//We make 2 channels for this.
	const numJobs = 5
	jobs := make(chan int, numJobs)
	results := make(chan int, numJobs)
	start := time.Now()
	//This starts up 3 workers, initially blocked because there are no jobs yet.
	for w := 1; w <= 3; w++ {
		go worker(w, jobs, results)
	}
	//Here we send 5 jobs and then close that channel to indicate that’s all the work we have.
	for j := 1; j <= numJobs; j++ {
		jobs <- j
	}
	close(jobs)
	//Finally we collect all the results of the work.
	//This also ensures that the worker goroutines have finished. An alternative way to wait for multiple goroutines is to use a WaitGroup.
	for a := 1; a <= numJobs; a++ {
		fmt.Printf("results:%d\n", <-results)
	}
	end := time.Now()
	fmt.Println("time consuming(s):", end.Sub(start).Seconds())
	time.Sleep(time.Second)
}

//Our running program shows the 5 jobs being executed by various workers.
//The program only takes about 2 seconds despite doing about 5 seconds of total work because
//there are 3 workers operating concurrently.
